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Meta: Muse Glimmer 30B

Source description (English)

Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...

View source on OpenRouter Hugging Face
Overview

Model specifications

Context
131,072 tokens
Maximum output
16,384 tokens
Architecture
text+image->text
Tokenizer
Other
Knowledge cutoff
Not provided
Moderated
No
OPENROUTER

Complete pricing

Synchronized OpenRouter rates. Token prices are shown per one million tokens.

Input
$0.3
per 1M tokens
Output
$1.2
per 1M tokens
Cache read
$0.04
per 1M tokens
API

Model configuration

Default parameters

temperature
1
top_p
0.95
top_k
64

Reasoning

Reasoning required
Yes
Default parameters
medium
Capabilities
xhigh, high, medium, low
API

Quick start

Set OPENROUTER_API_KEY locally. Python requires requests; JavaScript runs in Node.js. Keep the key on the server.

API documentation

curl --fail-with-body https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"meta/muse-glimmer-30b","messages":[{"role":"user","content":"Hello!"}]}'
Capabilities

Input → Output

Input
textimage
Output
text
Reasoning

No · xhigh · high · medium · low

API

Supported API parameters

frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Available providers

4 providers

Checked: September 21, 2026

Live providers on OpenRouter

Provider availability, latency, throughput and routing can change continuously. Open the source page for current operational data.

OpenRouter

Phala

Not provided
Context
131K
Maximum output
118K
Input
$0.3
Output
$1.1
Cache read
$0.04
Cache write
Not provided

DeepInfra

bf16
Context
131K
Maximum output
16K
Input
$0.3
Output
$1.2
Cache read
$0.04
Cache write
Not provided

Fireworks

Not provided
Context
131K
Maximum output
118K
Input
$0.35
Output
$1.5
Cache read
$0.04
Cache write
Not provided

Together

Not provided
Context
131K
Maximum output
118K
Input
$0.35
Output
$1.5
Cache read
$0.04
Cache write
Not provided
meta

4 models

All models
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Meta: Muse Voice Transcribe 1.0

Muse Voice Transcribe 1.0 is a synchronous speech-to-text model from Meta. It is suited for push-to-talk, endpointing, and speaker-aware transcription, with keyword biasing for domain terms and language biasing through...

Context
Not provided
Input
audio
Output
transcription
Audio seconds: $0.00005 per second
View model details →
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Meta: Muse Spark 1.3 Contributor

Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...

Context
1.0M
Input
text · image · video · file · audio
Output
text
Input: $0.1Output: $0.2per 1M tokens
View model details →
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Meta: Muse Spark 1.3

Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through...

Context
1.0M
Input
text · image · video · file · audio
Output
text
Input: $1.25Output: $4.25per 1M tokens
View model details →
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Meta: Muse Image

Muse Image is an agentic image generation model from Meta that generates and edits images from text and reference images. Unlike single-pass image models, it reasons before it renders, breaking...

Context
66K
Input
text · image
Output
image
Image output: $0.01 per image
View model details →